The complexity of searching a graph
Journal of the ACM (JACM)
Sweeping simple polygons with a chain of guards
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
On the monotonicity of games generated by symmetric submodular functions
Discrete Applied Mathematics - Submodularity
Planning Algorithms
Sweeping simple polygons with the minimum number of chain guards
Information Processing Letters
An annotated bibliography on guaranteed graph searching
Theoretical Computer Science
UAV target tracking using an adversarial iterative prediction
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Surveillance strategies for target detection with sweep lines
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Pursuit-evasion on trees by robot teams
IEEE Transactions on Robotics
GSST: anytime guaranteed search
Autonomous Robots
ESP: pursuit evasion on series-parallel graphs
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Connected searching of weighted trees
MFCS'10 Proceedings of the 35th international conference on Mathematical foundations of computer science
Search and pursuit-evasion in mobile robotics
Autonomous Robots
Hierarchical visibility for guaranteed search in large-scale outdoor terrain
Autonomous Agents and Multi-Agent Systems
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We consider the problem of detecting all moving and evading targets in 2.5D environments with teams of UAVs. Targets are assumed to be fast and omniscient while UAVs are only equipped with limited range detection sensors and have no prior knowledge about the location of targets. We present an algorithm that, given an elevation map of the environment, computes synchronized trajectories for the UAVs to guarantee the detection of all targets. The approach is based on coordinating the motion of multiple UAVs on sweep lines to clear the environment from contamination, which represents the possibility of an undetected target being located in an area. The goal is to compute trajectories that minimize the number of UAVs needed to execute the guaranteed search. This is achieved by converting 2D strategies, computed for a polygonal representation of the environment, to 2.5D strategies. We present methods for this conversion and consider cost of motion and visibility constraints. Experimental results demonstrate feasibility and scalability of the approach. Experiments are carried out on real and artificial elevation maps and provide the basis for future deployments of large teams of real UAVs for guaranteed search.